Remotely-sensed assessment of the impact of century-old biochar on chicory crop growth using high-resolution UAV-based imagery

Dehkordi, Ramin Heidarian; Denis, Antoine; Fouché, Julien; Burgeon, Victor; Cornélis, Jean-Thomas; Tychon, Bernard; Placencia‐Gomez, Edmundo; Meersmans, Jeroen

doi:10.1016/j.jag.2020.102147

Cited by 19 publications

(24 citation statements)

References 44 publications

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“…where Blue, Green, and Red show the digital number (DN) of the corresponding spectral channel of the visible spectrum, α and β are the classification threshold values with α representing the spectral difference between the green and red bands and β revealing the spectral difference between the green and red spectral channels. Similar to the finding of Heidarian Dehkordi et al [26], a threshold value of greater than 20 for both α and β was also reached in the present study through the visual inspection for the best vegetation classification. Canopy cover estimates were used as a potential discriminative parameter between the reference and century-old biochar plots in each acquisition date [26].…”

Section: Uav-based Crop Monitoringsupporting

confidence: 91%

“…Homogenous agricultural treatments were applied throughout the field. The detailed description is available in Heidarian Dehkordi et al [26], in which the same experimental configuration was followed by eleven 10 × 10 m century-old biochar plots (red squares in Figure 1) together with the corresponding reference plots (blue squares in Figure 1). Ground control point (GCP) targets, with known centroid coordinates through a real-time kinematic GPS, were deployed throughout the farm (Figure 1) to help with accurate geo-referencing of the data (i.e., 3 cm horizontal accuracy).…”

Section: Site Description and Data Acquisitionmentioning

confidence: 99%

“…Two remote sensing datasets (i.e., RGB and multispectral) were acquired during the 2019 growing season (Table 1) using high-resolution sensors onboard two UAV platforms to monitor the crop status over time ( Figure 2). RGB images were collected using a DJI Phantom 4 Pro and the multispectral images were obtained using a MicaSense RedEdge-M and downwelling light sensor, onboard a DJI Matrice 100 platform specifically designed by Heidarian Dehkordi et al [26], capturing blue (475 nm central wavelength), green (560 nm), red (668 nm), red-edge (717 nm), and near-infrared (840 nm) spectral channels with bandwidths of 20, 20, 10, 10, and 40 nm, respectively. The UAV platforms were programmed to fly at 65 and 60 m above ground altitude (AGL) with an airspeed of 5 and 7 ms −1 for RGB and multispectral sensors, respectively.…”

Section: Site Description and Data Acquisitionmentioning

confidence: 99%

“…Canopy cover was estimated from the acquired high-resolution RGB images ( Figure 2) based on the classification method by Heidarian Dehkordi et al [26]. This algorithm classifies the pixels in the orthomosaic to vegetation and non-vegetation classes according to the spectral differences between the green band and the blue and red bands as below:…”

Section: Uav-based Crop Monitoringmentioning

confidence: 99%

“…The studies listed above all explored the biochar effects on crop productivity. However, it is highly likely that biochar could affect crop development only during the green-up phase, while the harvested crop yield could remain unaffected [26]. More specifically, long-term biochar effects on crop performance and its development over the entire growing season have received much less attention than biochar effects on total crop productivity.…”

Section: Introductionmentioning

confidence: 99%

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Using UAV Collected RGB and Multispectral Images to Evaluate Winter Wheat Performance across a Site Characterized by Century-Old Biochar Patches in Belgium

et al. 2020

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Remote sensing data play a crucial role in monitoring crop dynamics in the context of precision agriculture by characterizing the spatial and temporal variability of crop traits. At present there is special interest in assessing the long-term impacts of biochar in agro-ecosystems. Despite the growing body of literature on monitoring the potential biochar effects on harvested crop yield and aboveground productivity, studies focusing on the detailed crop performance as a consequence of long-term biochar enrichment are still lacking. The primary objective of this research was to evaluate crop performance based on high-resolution unmanned aerial vehicle (UAV) imagery considering both crop growth and health through RGB and multispectral analysis, respectively. More specifically, this approach allowed monitoring of century-old biochar impacts on winter wheat crop performance. Seven Red-Green-Blue (RGB) and six multispectral flights were executed over 11 century-old biochar patches of a cultivated field. UAV-based RGB imagery exhibited a significant positive impact of century-old biochar on the evolution of winter wheat canopy cover (p-value = 0.00007). Multispectral optimized soil adjusted vegetation index indicated a better crop development over the century-old biochar plots at the beginning of the season (p-values < 0.01), while there was no impact towards the end of the season. Plant height, derived from the RGB imagery, was slightly higher for century-old biochar plots. Crop health maps were computed based on principal component analysis and k-means clustering. To our knowledge, this is the first attempt to quantify century-old biochar effects on crop performance during the entire growing period using remotely sensed data. Ground-based measurements illustrated a significant positive impact of century-old biochar on crop growth stages (p-value of 0.01265), whereas the harvested crop yield was not affected. Multispectral simplified canopy chlorophyll content index and normalized difference red edge index were found to be good linear estimators of harvested crop yield (p-value(Kendall) of 0.001 and 0.0008, respectively). The present research highlights that other factors (e.g., inherent pedological variations) are of higher importance than the presence of century-old biochar in determining crop health and yield variability.

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Section: Uav-based Crop Monitoringsupporting

confidence: 91%

Section: Site Description and Data Acquisitionmentioning

confidence: 99%

Section: Site Description and Data Acquisitionmentioning

confidence: 99%

Section: Uav-based Crop Monitoringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using UAV Collected RGB and Multispectral Images to Evaluate Winter Wheat Performance across a Site Characterized by Century-Old Biochar Patches in Belgium

et al. 2020

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UAV image acquisition and processing for high‐throughput phenotyping in agricultural research and breeding programs

Bongomin,

Lamo,

Guina

et al. 2024

The Plant Phenome Journal

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We are in a race against time to combat climate change and increase food production by 70% to feed the ever‐growing world population, which is expected to double by 2050. Agricultural research plays a vital role in improving crops and livestock through breeding programs and good agricultural practices, enabling sustainable agriculture and food systems. While advanced molecular breeding technologies have been widely adopted, phenotyping as an essential aspect of agricultural research and breeding programs has seen little development in most African institutions and remains a traditional method. However, the concept of high‐throughput phenotyping (HTP) has been gaining momentum, particularly in the context of unmanned aerial vehicle (UAV)‐based phenotyping. Although research into UAV‐based phenotyping is still limited, this paper aimed to provide a comprehensive overview and understanding of the use of UAV platforms and image analytics for HTP in agricultural research and to identify the key challenges and opportunities in this area. The paper discusses field phenotyping concepts, UAV classification and specifications, use cases of UAV‐based phenotyping, UAV imaging systems for phenotyping, and image processing and analytics methods. However, more research is required to optimize UAVs’ performance for image data acquisition, as limited studies have focused on the effect of UAVs’ operational parameters on data acquisition.

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Young and century-old biochars strongly affect nutrient cycling in a temperate agroecosystem

Burgeon

Fouché

Garré

et al. 2022

Agriculture, Ecosystems & Environment

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Remotely-sensed assessment of the impact of century-old biochar on chicory crop growth using high-resolution UAV-based imagery

Cited by 19 publications

References 44 publications

Using UAV Collected RGB and Multispectral Images to Evaluate Winter Wheat Performance across a Site Characterized by Century-Old Biochar Patches in Belgium

Using UAV Collected RGB and Multispectral Images to Evaluate Winter Wheat Performance across a Site Characterized by Century-Old Biochar Patches in Belgium

UAV image acquisition and processing for high‐throughput phenotyping in agricultural research and breeding programs

Young and century-old biochars strongly affect nutrient cycling in a temperate agroecosystem

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